chore: import upstream snapshot with attribution

examples/agent-ollama/main.go

@@ -0,0 +1,246 @@
+// Agent Ollama — a self-contained agent powered by Ollama Cloud.
+//
+// This example demonstrates the full harness loop — service tools, custom
+// tools, agent memory, guardrails, and streaming — using the Ollama
+// provider with gpt-oss:120b on Ollama Cloud.
+//
+// It creates a "knowledge" service with two endpoints (Add, Search) that
+// the agent discovers as tools, plus a custom "current_time" tool. The
+// agent answers natural-language questions by calling those tools.
+//
+// Run (Ollama Cloud — default):
+//
+//	OLLAMA_API_KEY=your-key go run main.go
+//
+// Run (local Ollama):
+//
+//	OLLAMA_BASE_URL=http://localhost:11434 \
+//	OLLAMA_MODEL=llama3.2 \
+//	go run main.go
+package main
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"os"
+	"strings"
+	"sync"
+	"time"
+
+	"go-micro.dev/v6"
+	"go-micro.dev/v6/agent"
+)
+
+// ---------------------------------------------------------------------------
+// knowledge service — a tiny in-memory knowledge base
+// ---------------------------------------------------------------------------
+
+type KnowledgeEntry struct {
+	ID      string `json:"id" description:"Unique entry identifier"`
+	Topic   string `json:"topic" description:"Topic or category"`
+	Content string `json:"content" description:"The knowledge content"`
+}
+
+type AddKnowledgeRequest struct {
+	Topic   string `json:"topic" description:"Topic or category (required)"`
+	Content string `json:"content" description:"The knowledge content (required)"`
+}
+
+type AddKnowledgeResponse struct {
+	Entry *KnowledgeEntry `json:"entry" description:"The added entry"`
+}
+
+type SearchKnowledgeRequest struct {
+	Topic   string `json:"topic,omitempty" description:"Filter by topic (optional)"`
+	Keyword string `json:"keyword,omitempty" description:"Search keyword in content (optional)"`
+}
+
+type SearchKnowledgeResponse struct {
+	Entries []*KnowledgeEntry `json:"entries" description:"Matching entries"`
+}
+
+type KnowledgeService struct {
+	mu      sync.RWMutex
+	entries []*KnowledgeEntry
+	nextID  int
+}
+
+// Add stores a new knowledge entry.
+//
+// @example {"topic": "go", "content": "Go interfaces are implicit."}
+func (s *KnowledgeService) Add(ctx context.Context, req *AddKnowledgeRequest, rsp *AddKnowledgeResponse) error {
+	s.mu.Lock()
+	defer s.mu.Unlock()
+	s.nextID++
+	e := &KnowledgeEntry{
+		ID:      fmt.Sprintf("kb-%d", s.nextID),
+		Topic:   req.Topic,
+		Content: req.Content,
+	}
+	s.entries = append(s.entries, e)
+	rsp.Entry = e
+	return nil
+}
+
+// Search finds knowledge entries by topic or keyword.
+//
+// @example {"topic": "go"}
+// @example {"keyword": "interface"}
+func (s *KnowledgeService) Search(ctx context.Context, req *SearchKnowledgeRequest, rsp *SearchKnowledgeResponse) error {
+	s.mu.RLock()
+	defer s.mu.RUnlock()
+	for _, e := range s.entries {
+		if req.Topic != "" && !strings.EqualFold(e.Topic, req.Topic) {
+			continue
+		}
+		if req.Keyword != "" && !strings.Contains(strings.ToLower(e.Content), strings.ToLower(req.Keyword)) {
+			continue
+		}
+		rsp.Entries = append(rsp.Entries, e)
+	}
+	return nil
+}
+
+// ---------------------------------------------------------------------------
+// main
+// ---------------------------------------------------------------------------
+
+func main() {
+	// Ollama Cloud is the default. Override with env vars for local Ollama.
+	baseURL := os.Getenv("OLLAMA_BASE_URL")
+	if baseURL == "" {
+		baseURL = "https://ollama.com/v1"
+	}
+	model := os.Getenv("OLLAMA_MODEL")
+	if model == "" {
+		model = "gpt-oss:120b"
+	}
+	apiKey := os.Getenv("OLLAMA_API_KEY")
+
+	fmt.Println("╔══════════════════════════════════════════╗")
+	fmt.Println("║       Ollama-Powered Go Micro Agent      ║")
+	fmt.Println("╚══════════════════════════════════════════╝")
+	fmt.Println()
+	fmt.Printf("  Ollama URL:  %s\n", baseURL)
+	fmt.Printf("  Model:       %s\n", model)
+	if apiKey != "" {
+		fmt.Printf("  API Key:     (set)\n")
+	} else {
+		fmt.Printf("  API Key:     (none — set OLLAMA_API_KEY)\n")
+	}
+	fmt.Println()
+
+	// 1. Start the knowledge service. Its handlers become agent tools.
+	svc := micro.NewService("knowledge")
+	svc.Handle(new(KnowledgeService))
+	go svc.Run()
+
+	// Give the service a moment to register.
+	time.Sleep(2 * time.Second)
+
+	// 2. Create the agent. It discovers the knowledge service endpoints
+	//    as tools automatically, plus gets a custom "current_time" tool.
+	ag := micro.NewAgent("ollama-assistant",
+		micro.AgentServices("knowledge"),
+		micro.AgentPrompt(
+			"You are a helpful knowledge assistant. You can search and add to "+
+				"a knowledge base using the knowledge service tools. "+
+				"When asked about the current time, use the current_time tool. "+
+				"Be concise and factual.",
+		),
+		micro.AgentProvider("ollama"),
+		micro.AgentModel(model),
+		micro.AgentAPIKey(apiKey),
+		micro.AgentBaseURL(baseURL),
+		micro.AgentMaxSteps(10),
+		micro.AgentLoopLimit(3),
+		// Custom tool — any function, not tied to a service.
+		agent.WithTool(
+			"current_time",
+			"Get the current date and time in a human-readable format",
+			map[string]any{
+				"timezone": map[string]any{
+					"type":        "string",
+					"description": "Optional timezone (defaults to local)",
+				},
+			},
+			func(ctx context.Context, input map[string]any) (string, error) {
+				tz, _ := input["timezone"].(string)
+				if tz == "" {
+					return time.Now().Format("2006-01-02 15:04:05 MST"), nil
+				}
+				loc, err := time.LoadLocation(tz)
+				if err != nil {
+					return "", fmt.Errorf("unknown timezone: %s", tz)
+				}
+				return time.Now().In(loc).Format("2006-01-02 15:04:05 MST"), nil
+			},
+		),
+	)
+
+	// 3. Seed initial knowledge via the agent's first question.
+	questions := []string{
+		"What time is it now?",
+		"Add a new knowledge entry: topic 'go', content 'Go interfaces are implicit — a type implements an interface by having the required methods.'",
+		"Add another entry: topic 'go', content 'Go is a statically typed, compiled language designed at Google.'",
+		"Add another entry: topic 'ai', content 'Large language models generate text by predicting the next token in a sequence.'",
+		"Search the knowledge base for entries about Go.",
+		"Search for everything in the knowledge base.",
+	}
+
+	fmt.Println("─── Agent Demo ───")
+	fmt.Println()
+
+	for i, q := range questions {
+		fmt.Printf("Q%d: %s\n", i+1, q)
+		fmt.Print("A: ")
+
+		resp, err := ag.Ask(context.Background(), q)
+		if err != nil {
+			fmt.Printf("error: %v\n", err)
+			fmt.Println()
+			continue
+		}
+
+		// Show tool calls the agent made.
+		if len(resp.ToolCalls) > 0 {
+			for _, tc := range resp.ToolCalls {
+				args, _ := json.Marshal(tc.Input)
+				fmt.Printf("  [tool] %s(%s)\n", tc.Name, string(args))
+			}
+		}
+
+		fmt.Println(resp.Reply)
+		if resp.Reply == "" && len(resp.ToolCalls) == 0 {
+			fmt.Println("(no response)")
+		}
+		fmt.Println()
+	}
+
+	// 4. Streaming demonstration.
+	fmt.Println("─── Streaming Demo ───")
+	fmt.Println()
+	streamQ := "Explain what Go Micro is in two sentences."
+	fmt.Printf("Q: %s\n", streamQ)
+	fmt.Print("A: ")
+
+	stream, err := ag.Stream(context.Background(), streamQ)
+	if err != nil {
+		fmt.Printf("stream error: %v\n", err)
+	} else {
+		for {
+			chunk, err := stream.Recv()
+			if err != nil {
+				break
+			}
+			if chunk.Reply != "" {
+				fmt.Print(chunk.Reply)
+			}
+		}
+		fmt.Println()
+	}
+
+	fmt.Println()
+	fmt.Println("Done.")
+}